Book contents
- Frontmatter
- Contents
- List of Contributors
- Foreword
- Acknowledgements
- Part I Growth data and growth studies: characteristics and methodological issues
- 1 Why study child growth and maturation?
- 2 The human growth curve: distance, velocity and acceleration
- 3 Sampling for growth studies and using growth data to assess, monitor and survey disease in epidemiological settings
- 4 Measuring growth
- 5 Measuring maturity
- 6 Measuring body composition
- Part II Non-parametric and parametric approaches for individual growth
- Part III Methods for population growth
- Part IV Special topics
- Index
3 - Sampling for growth studies and using growth data to assess, monitor and survey disease in epidemiological settings
Published online by Cambridge University Press: 17 August 2009
- Frontmatter
- Contents
- List of Contributors
- Foreword
- Acknowledgements
- Part I Growth data and growth studies: characteristics and methodological issues
- 1 Why study child growth and maturation?
- 2 The human growth curve: distance, velocity and acceleration
- 3 Sampling for growth studies and using growth data to assess, monitor and survey disease in epidemiological settings
- 4 Measuring growth
- 5 Measuring maturity
- 6 Measuring body composition
- Part II Non-parametric and parametric approaches for individual growth
- Part III Methods for population growth
- Part IV Special topics
- Index
Summary
Sampling for growth studies
The purpose of sampling is to take measurements on a representative portion of the population so that the whole population does not have to be measured. Each observation in the sample can be thought of as representing a certain number of population members. The reciprocal of the number in the population represented by an observation is the sampling proportion.
Sampling schemes
Most schemes for obtaining samples fall into one of three categories. Sampling can be done: (1) from a complete or nearly complete list; (2) from a set of people who go somewhere or do something; or (3) in two or more stages (Fowler, 1984). The first category implies that there is a list of the population available in advance from which then to take a sample. Examples of the second category are sampling children who get services from a hospital or who shop at a store with a parent. The third category includes schemes such as sampling, in turn, states or provinces, counties or departments, neighbourhoods or villages, households, and then individuals.
Characteristics to evaluate sampling
Three characteristics important for evaluating a sampling scheme are: (1) comprehensiveness; (2) known probability of (or equal) selection; and (3) efficiency (Fowler, 1984). Comprehensiveness refers to whether everyone in the population of interest from which the sample is to be drawn had a chance to be selected into the sample. That is, a sampling scheme is not comprehensive if some people in the population are excluded from being possibly sampled.
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- Chapter
- Information
- Methods in Human Growth Research , pp. 55 - 67Publisher: Cambridge University PressPrint publication year: 2004